Bat algorithm explained

The Bat algorithm is a metaheuristic algorithm for global optimization. It was inspired by the echolocation behaviour of microbats, with varying pulse rates of emission and loudness.^{[1] [2]} The Bat algorithm was developed by Xin-She Yang in 2010.^[3]

Metaphor

The idealization of the echolocation of microbats can be summarized as follows: Each virtual bat flies randomly with a velocity

v _{i} at position (solution) x _{i} with a varying frequency or wavelength and loudness A _{i} . As it searches and finds its prey, it changes frequency, loudness and pulse emission rate r . Search is intensified by a local random walk. Selection of the best continues until certain stop criteria are met. This essentially uses a frequency-tuning technique to control the dynamic behaviour of a swarm of bats, and the balance between exploration and exploitation can be controlled by tuning algorithm-dependent parameters in bat algorithm.

A detailed introduction of metaheuristic algorithms including the bat algorithm is given by Yang^[4] where a demo program in MATLAB/GNU Octave is available, while a comprehensive review is carried out by Parpinelli and Lopes.^[5] A further improvement is the development of an evolving bat algorithm (EBA) with better efficiency.^[6]

See also

• List of metaphor-based metaheuristics

Further reading

• Yang, X.-S. (2014), Nature-Inspired Optimization Algorithms, Elsevier.

Notes and References

1. J. D. Altringham, Bats: Biology and Behaviour, Oxford University Press, (1996).
2. P. Richardson, Bats. Natural History Museum, London, (2008)
3. Yang . X. S. . 2010 . A New Metaheuristic Bat-Inspired Algorithm, in: Nature Inspired Cooperative Strategies for Optimization (NISCO 2010) . 1004.4170. Studies in Computational Intelligence . 284 . 65–74 . 2010arXiv1004.4170Y .
4. Yang, X. S., Nature-Inspired Metaheuristic Algorithms, 2nd Edition, Luniver Press, (2010).
5. Parpinelli . R. S. . Lopes . H. S. . 16866891 . 2011 . New inspirations in swarm intelligence: A survey. International Journal of Bio-Inspired Computation. 3 . 1–16 . 10.1504/ijbic.2011.038700.
6. Tsai . P. W. . Pan . J. S. . Liao . B. Y. . Tsai . M. J. . Istanda . V. . 2012 . Bat algorithm inspired algorithm for solving numerical optimization problems . Applied Mechanics and Materials . 148-149 . 134–137 . 10.4028/www.scientific.net/amm.148-149.134. 2011AMM...148..134T .